bert-base-uncased-glue-mrpc-camilovg
This model is a fine-tuned version of bert-base-uncased on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.3969
- Accuracy: 0.8529
- F1: 0.8929
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5207 | 1.09 | 500 | 0.3969 | 0.8529 | 0.8929 |
0.2963 | 2.18 | 1000 | 0.5402 | 0.8725 | 0.9110 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for camiloTel0410/bert-base-uncased-glue-mrpc-camilovg
Base model
google-bert/bert-base-uncasedDataset used to train camiloTel0410/bert-base-uncased-glue-mrpc-camilovg
Evaluation results
- Accuracy on gluevalidation set self-reported0.853
- F1 on gluevalidation set self-reported0.893